Abstract

The objective of this systematic review (SR) with meta-analysis (MA) was to identify the dietary patterns of the population, regarding ethnicity and gender, and their association with the metabolic syndrome and its risk factors (MetS-RF). The literature search was performed using Medline, Scopus, Ebsco, SciELO, and BVS databases. Studies with adult participants that identified dietary patterns associated with MetS-RF were included. Pooled odds ratio (OR) and 95%CI were calculated using a random-effect, generic inverse variance method. Statistical heterogeneity and publication bias were explored. The dietary patterns were classified as healthy or unhealthy. Studies were categorized into three groups: Women (all ethnicities), Afro-descendant (men and women), and General Population (both genders and ethnicity). Among the articles found (n=8,496), 22 integrated the SR and 11 the MA. The adherence to the healthy dietary pattern was negatively associated (protective factor) with MetS-RF only in the General Population (OR=0.77; 95%CI: 0.61-0.98). Nevertheless, the unhealthy dietary pattern was associated with the higher prevalence of MetS-RF in all analyzed groups. It was concluded that an unhealthy eating pattern increases the chances of SM-RF in adults, regardless of gender and ethnicity.

Key words:
Metabolic syndrome; Feeding behavior; Western diet

Resumo

Esta revisão sistemática (RS) com meta-análise (MA) teve por objetivo identificar os padrões alimentares da população, segundo sexo e etnia, e sua associação com a síndrome metabólica e seus fatores de risco (SM-FR). Foram consultadas as seguintes bases de dados: Medline, Scopus, Ebsco, SciELO e BVS. Foram incluídos estudos com participantes adultos e que identificaram padrões alimentares associados à SM-FR. Na MA empregou-se o modelo de efeitos aleatórios para estimativa do odds ratio (OR) combinado. A heterogeneidade estatística e o viés de publicação foram explorados. Os padrões alimentares foram agrupados em saudável ou não saudável. Conforme a composição das amostras, os estudos foram assim categorizados: Mulheres (sem definição de etnia), Afrodescendentes (homens e mulheres), e População Geral (ambos os sexos e etnia). Foram encontrados 8.496 artigos, dos quais 22 compuseram a RS e 11 a MA. A adesão ao padrão alimentar saudável associou-se negativamente com SM-FR (fator de proteção) apenas para População Geral (OR=0,77; IC95%: 0,61-0,98). No entanto, o padrão alimentar não saudável esteve associado a maiores prevalências de SM-FR em todos os grupos analisados. Concluiu-se que um padrão alimentar não saudável aumenta as chances de SM-FR em adultos, independentemente de gênero e etnia.

Palavras-chave:
Síndrome metabólica; Comportamento alimentar; Dieta ocidental

Introduction

The dietary pattern can be defined as the set of food and beverages that are usually consumed by individuals and populations¹1 United States Department of Agriculture (USDA). A Series of Systematic Reviews on the Relationship Between Dietary Patterns and Health Outcomes. Washington, D.C.: USDA; 2014.^,22 Schulze MB, Martínez-González MA, Fung TT, Lichtenstein AH, Forouhi NG. Food-based dietary patterns and chronic disease prevention. BMJ 2018; 361:k2396.. Unhealthy dietary patterns, allied to a sedentary lifestyle, contribute to the increased prevalence of chronic non-communicable diseases (NCDs)³3 Mozaffarian D. Dietary and Policy Priorities for Cardiovascular Disease, Diabetes, and Obesity - A Comprehensive Review. Circulation 2016; 133(2):187-225., for instance, metabolic syndrome (MetS). This is characterized by the presence of certain conditions such as central obesity, dyslipidemia, hypertension (SAH), insulin resistance, and hyperglycemia⁴4 Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, Gordon DJ, Krauss RM, Savage PJ, Smith SC, Spertus JA, Costa F. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute scientific statement. Curr Opin Cardiol 2006; 21(1):1-6..

The association between dietary patterns and MetS has been quite studied. Some studies show it as a protective factor, while others indicate an increased risk of developing MetS⁵5 Rodríguez-Monforte M, Sánchez E, Barrio F, Costa B, Flores-Mateo G. Metabolic syndrome and dietary patterns: a systematic review and meta-analysis of observational studies. Eur J Nutr 2017; 56(3):925-947.

6 Deshmukh-Taskar PR, O'Neil CE, Nicklas TA, Yang SJ, Liu Y, Gustat J, Berenson GS. Dietary patterns associated with metabolic syndrome, sociodemographic and lifestyle factors in young adults: the Bogalusa Heart Study. Public Health Nutr 2009; 12(12):2493-2503.

7 Godos J, Bella F, Torrisi A, Sciacca S, Galvano F, Grosso G. Dietary patterns and risk of colorectal adenoma: a systematic review and meta-analysis of observational studies. J Hum Nutr Diet 2016; 29(6):757-767.^-88 Fabiani R, Naldini G, Chiavarini M. Dietary Patterns and Metabolic Syndrome in Adult Subjects: A Systematic Review and Meta-Analysis. Nutrients 2019; 11(9):2056.. A healthy dietary pattern, as the one based on characteristic food of the Mediterranean diet, improves the HDL profile and of the MetS components⁹9 Castro-Barquero S, Tresserra-Rimbau A, Vitelli-Storelli F, Doménech M, Salas-Salvadó J, Martín-Sánchez V, Rubín-García M, Buil-Cosiales P, Corella D, Fitó M, Romaguera D, Vioque J, Alonso-Gómez ÁM, Wärnberg J, Martínez JA, Serra-Majem L, Tinahones FJ, Lapetra J, Pintó X, Tur JA, Garcia-Rios A, García-Molina L, Delgado-Rodriguez M, Matía-Martín P, Daimiel L, Vidal J, Vázquez C, Cofán M, Romanos-Nanclares A, Becerra-Tomas N, Barragan R, Castañer O, Konieczna J, González-Palacios S, Sorto-Sánchez C, Pérez-López J, Zulet MA, Bautista-Castaño I, Casas R, Gómez-Perez AM, Santos-Lozano JM, Rodríguez-Sanchez MÁ, Julibert A, Martín-Calvo N, Hernández-Alonso P, Sorlí J V, Sanllorente A, Galmés-Panadés AM, Cases-Pérez E, Goicolea-Güemez L, Ruiz-Canela M, Babio N, Hernáez Á, Lamuela-Raventós RM, Estruch R. Dietary Polyphenol Intake is Associated with HDL-Cholesterol and A Better Profile of other Components of the Metabolic Syndrome: A PREDIMED-Plus Sub-Study. Nutrients 2020;12(3):689.^,1010 Castro-Barquero S, Ruiz-León AM, Sierra-Pérez M, Estruch R, Casas R. Dietary Strategies for Metabolic Syndrome: A Comprehensive Review. Nutrients 2020; 12(10):2983.. The Brazilian cardioprotective dietary pattern¹¹11 Martins PR, Moreira AS, Santos EM, Rodrigues LF, Weber B. Effect of the Brazilian Cardioprotective Nutritional Program on the Quality of Life of Atherosclerotic Disease Patients. Int J Cardiovasc Sci 2021; 34(6):620-631. contributes to the reduction of LDL levels. In contrast, an unhealthy pattern, characterized by the presence of fried meat, processed meat, sugars, fast food, alcoholic beverages, among others, is associated with a greater risk for MetS¹²12 Liu L, Nettleton JA, Bertoni AG, Bluemke DA, Lima JA, Szklo M. Dietary pattern, the metabolic syndrome, and left ventricular mass and systolic function: the Multi-Ethnic Study of Atherosclerosis123. Am J Clin Nutr 2009; 90(2):362-368.^,1313 Heidemann C, Scheidt-Nave C, Richter A, Mensink GB. Dietary patterns are associated with cardiometabolic risk factors in a representative study population of German adults. Br J Nutr 2011; 106(8):1253-1262..

Studies on the relationship between diet and NCDs have increased¹⁴14 Hu FB. Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol 2002; 13(1):3-9., but most of the research has been conducted in North America, Europe, and Asia¹⁴14 Hu FB. Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol 2002; 13(1):3-9.

15 Grosso G, Bella F, Godos J, Sciacca S, Del Rio D, Ray S, Galvano F, Giovannucci EL. Possible role of diet in cancer: systematic review and multiple meta-analyses of dietary patterns, lifestyle factors, and cancer risk. Nutr Rev 2017; 75(6):405-419.^-1616 Michels KB, Schulze MB. Can dietary patterns help us detect diet-disease associations? Nutr Res Rev 2005; 18(2):241-248., with minimal focus on Afro-descendant populations, particularly those that differentiate results by gender. Research carried out in the USA revealed that the black population had a greater probability of adopting an unhealthy dietary pattern compared to the white population¹⁷17 Couch CA, Gray MS, Shikany JM, Howard VJ, Howard G, Long DL, McClure LA, Manly JJ, Cushman M, Zakai NA, Pearson KE, Levitan EB, Judd SE. Correlates of a southern diet pattern in a national cohort study of blacks and whites: the REasons for Geographic And Racial Differences in Stroke (REGARDS) study. Br J Nutr 2021; 126(12):1904-1910..

Certain MetS components, for instance, SAH, are more prevalent in Afro-descendant individuals¹⁸18 Munroe P, Barnes M, Caulfield M. Advances in blood pressure genomics. Circ Res 2013; 112(10):1365-1379., but little is known about the MetS characteristics in black populations¹⁹19 Mussi FC, Palmeira CS, Santos CA, Guimarães AC, Lima ML, Nascimento TS. Effect of nursing telemonitoring on the knowledge of obese women: clinical trial. Rev Bras Enferm 2019; 72(Supl. 3):212-219.. Furthermore, there seems to be a higher susceptibility of the women population to MetS²⁰20 Silva-Júnior AC, Cruz DP, Souza Junior EV, Souza RR, Moreira RM, Santos ISC. Repercussões da prevalencia da síndrome metabólica em adultos e idosos no contexto da atenção primária. Rev Salud Publica 2020; 20(6):735-740.^,2121 Ramires EK, Menezes RC, Longo-Silva G, Santos TG, Marinho PM, Silveira JA, RamiPrevalência e Fatores Associados com a Síndrome Metabólica na População Adulta Brasileira: Pesquisa Nacional de Saúde - 2013. Arq Bras Cardiol 2018; 110(5):455-466.. In this context, little is known about the dietary patterns practiced by this public, which indicates the necessity of such relations to be further clarified.

This study aimed to identify the dietary patterns of the population, according to ethnicity and gender, and their association with the MetS or its risk factors (MetS-RF).

Methods

This is a systematic review (SR) with meta-analysis (MA) developed to answer the following question: Which dietary patterns adopted by women and afro-descendants are associated with MetS-RF? In the search for articles, an adaptation of the PICO strategy²²22 Santos CM, Pimenta CA, Nobre MR. A estratégia PICO para a construção da pergunta de pesquisa e busca de evidências. Rev Lat Am Enferm 2007; 15(3):508-511. was used. This study used “exposure” instead of “intervention” due to its observational nature and did not include a “comparator”, which is typically used in efficacy comparison studies. The recommendations contained in PRISMA were followed²³23 Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, Shamseer L, Tetzlaff JM, Akl EA, Brennan SE, Chou R, Glanville J, Grimshaw JM, Hróbjartsson A, Lalu MM, Li T, Loder EW, Mayo-Wilson E, McDonald S, McGuinness LA, Stewart LA, Thomas J, Tricco AC, Welch VA, Whiting P, Moher D. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021; 372:n71.. The research protocol was previously registered (PROSPERO ID CRD42020148478).

Search Strategy

The search for articles was carried out on the following electronic databases: MEDLINE (via PubMed), SciELO, Virtual Health Library (VHL - the Brazilian Virtual Health Library - BVS); EBSCO and, Scopus. The following limits were used: human beings, age ≥18 years, and English, Portuguese and Spanish languages. The terms employed in the search were identified on the DeCS and the MeSH. In MEDLINE (PubMed) the search strategy was established using the alternative “advanced search” and the logical operators OR and AND. Thus, having MEDLINE as a reference, the search strategy was organized as follows: ((Adult# OR “middle age” OR “young adult” OR Women)) AND (“African Continental Ancestry Group” OR Black OR negro OR “Negroid Race” OR “Races, Negroid” OR “black-slaves descendant” OR Quilombolas) AND (Eating OR “food analysis” OR food# OR “Feeding Behavior” OR “Feeding Behaviors” OR “Feeding Patterns” OR “Feeding Pattern” OR “food habit” OR “food habits” OR Diet OR “food consumption”) AND (“Metabolic Syndrome” OR “Metabolic Syndrome X” OR “excess weight” OR overweight OR obesity OR “abdominal obesity” OR hypertension OR “High Blood Pressure” OR “dyslipidemia” OR “total cholesterol” OR “triglycerides” OR “Cholesterol, HDL” OR “High Density Lipoprotein Cholesterol” OR “Cholesterol, LDL” OR “Low Density Lipoprotein Cholesterol” OR “Cholesterol, VLDL” OR “Very Low Density Lipoprotein Cholesterol” OR “Diabetes Mellitus” OR “Diabetes” OR Hyperglycemia OR “insulin resistance”). For the other databases, the necessary adaptations were made, according to their specificities.

The reference lists of the selected articles were also examined, as well as the review articles found when applying the search strategy. Additionally, the BVS database was consulted, which contains works from postgraduate programs (theses and dissertations) and other types of productions classified within the scope of grey literature.

Eligibility criteria

Observational study; having analyzed women (>18 years); studies that included Afro-descendant individuals, studies that identified dietary patterns associated with risk factors for MetS or itself, and articles which defined dietary patterns using statistical techniques a posteriori, such as a factor analysis (FA), principal component analysis (PCA) and cluster analysis.

Selection of articles

Duplicate articles were checked and, subsequently, two evaluators (LBB and IRSG) conducted the selection of publications recovered through the initial search strategy. This selection was based on the reading of the titles and abstracts, and it was conducted independently, by applying the pre-defined eligibility criteria. The selected articles at this stage were assessed by reading the full text, also independently by the two authors. In case of disagreements in any selection stage, these were solved by consensus after the discussion between the peers. When no agreement was reached, the divergences were solved by two other researchers (HSF and TAS).

The Rayyan application (Rayyan QCRI: https://www.rayyan.ai/) was used for duplicate articles by title and abstract.

Data extraction

The results of data extraction, performed independently by two reviewers (LBB and IRSG), were compared and discrepancies were resolved by consensus. When this did not happen, a third researcher (EAS) was called to decide. The following information was extracted in Excel spreadsheet: publication year; study location; period of realization; methodological design; target-public characteristics (age, women percentage, afro-descendants percentage); sample size; exposures and outcomes assessed; MetS risk factors; assessment methods of food consumption; the statistical method used in the definition of food consumption pattern; the name given to dietary patterns and their characteristics; adherence categories to the dietary pattern (dichotomous, tertile, Quartile or Quintile); risk estimates with 95%CI for different adherence categories to the dietary patterns and significance level of the associations (p-value). Additionally, the necessary information was extracted to assess the quality of the articles.

Methodological quality assessment of the articles

The quality of the selected studies was assessed independently by three researchers (LBB, IRSG, and NBRV) by using the Quality Assessment Tool for Quantitative Studies of the Effective Public Health Practice Project (EPHPP)²⁴24 Thomas BH, Ciliska D, Dobbins M, Micucci S. A process for systematically reviewing the literature: providing the research evidence for public health nursing interventions. Worldviews Evidence Based Nurs 2004; 1(3):176-184.. In case of divergences, a fourth reviewer was consulted (EAS).

The EPHPP comprises 22 different items divided into eight blocks: selection bias, study design, confounding factors, blinding, data collection method, dropouts, and withdrawals, the integrity of intervention, and analysis. Nevertheless, for this study, two blocks were not considered: the integrity of intervention, and analysis. For some of these blocks, the classification criteria were adjusted based on the study types included in this review²⁵25 Akbaraly TN, Singh-Manoux A, Marmot MG, Brunner EJ. Education Attenuates the Association between Dietary Patterns and Cognition. Dement Geriatr Cogn Disord 2009; 27(2):147.^,2626 Paula WK, Samico IC, Caminha FC, Batista Filho M, Silva SL. Avaliação da atenção básica à saúde sob a ótica dos usuários: uma revisão sistemática. Rev Esc Enferm USP 2016; 50(2):0335-0345.. As to study design, as cross-sectional studies were included, which by nature, do not have a control or intervention group, to not classify them as weak in this block, the assessment was designated as “not applicable”. At the “blinding” criterion, all studies were classified as moderate.

Each one of the blocks was assessed and classified as strong, moderate, or weak, and, in the end, the studies were designated as high/strong quality when no assessment item of the study was categorized as of low/weak evidence; moderate when only one of the criteria was defined as low/weak and; weak when it was attributed low/weak pattern to two or more items of the analyzed criteria.

Evidence quality assessment

The evidence quality of the present MA was assessed by using the NutriGrade scoring system²⁷27 Schwingshackl L, Knüppel S, Schwedhelm C, Hoffmann G, Missbach B, Stelmach-Mardas M, Dietrich S, Eichelmann F, Kontopanteils E, Iqbal K, Aleksandrova K, Lorkowski S, Leitzmann MF, Kroke A, Boeing H. Perspective: NutriGrade: A Scoring System to Assess and Judge the Meta-Evidence of Randomized Controlled Trials and Cohort Studies in Nutrition Research. Adv Nutr 2016; 7(6):994.. The assessment was conducted based on 8 criteria: 1) risk of bias, 2) precision, 3) heterogeneity, 4) directness, 5) publication bias, 6) funding bias, 7) effect size, and 8) dose-response. The maximum scoring for the MA is 10 points being the evidence quality classified as follows: a) very low evidence (scoring<4), b) low evidence (from 4 to 5.99 points), c) moderate quality (from 6 to 7.99 points), and d) high evidence quality (scoring≥8).

Statistical analysis

The MA was conducted to combine the results and compare the odds ratio (OR) for MetS-RF according to the higher categories of consumption of healthy or unhealthy dietary patterns, in comparison to the lower categories of consumption of these patterns. As a result of the dietary patterns being specific for each population and, thus, having distinct nomenclatures, only patterns that shared the majority of food and with similar factorial charges were considered.

The generic inverse variance method was used. Relative risk (RR) or hazard ratio (HR) were considered directly as OR estimates⁷7 Godos J, Bella F, Torrisi A, Sciacca S, Galvano F, Grosso G. Dietary patterns and risk of colorectal adenoma: a systematic review and meta-analysis of observational studies. J Hum Nutr Diet 2016; 29(6):757-767.^,88 Fabiani R, Naldini G, Chiavarini M. Dietary Patterns and Metabolic Syndrome in Adult Subjects: A Systematic Review and Meta-Analysis. Nutrients 2019; 11(9):2056.. Random effect models were used to calculate ORs grouped with their respective 95%CI. Heterogeneity was assessed by using the Q test at a significance level of 10% and I² statistics, which produces results ranging from 0% to 100%: I²=0% to <25%, no/low heterogeneity; I² from ≥25% to <50%, moderate heterogeneity; I²>50%, high heterogeneity²⁸28 Higgins JPT, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med 2002; 21(11):1539-1558..

The analyses were pre-stratified based on the characteristics of the respective samples and, in this study, were identified as follows:

The sensitivity analysis by excluding one study at a time was performed to assess the influence of one single study on the estimate and its contribution as a source of heterogeneity. Analyses of sub-groups were also performed to verify the contribution in the heterogeneity of the following factors: design, study location, and percentage of women or Afro-descendant individuals in the sample.

The publication bias was assessed by visual analysis of funnel plots. All analyses were performed using the software Revman version 5.4.

Results

A total of 8,496 articles were identified. Of these, 83 were submitted to full-text assessment; 67 were considered non-adherent to the inclusion criteria. Thus, 16 studies were selected. After exploring the reference lists in these articles, other six studies were included. Therefore, 22 publications were included in this SR (Figure 1).

Characteristics of the studies and quality assessment

The publications of manuscripts that involved the researched theme began in 2004, being 2009 the year presenting the greatest number (n=4) of publications (Chart 1).

The period of collection of the analyzed data in the selected studies varied between the years 1992²⁹29 Liese AD, Schulz M, Moore CG, Mayer-Davis EJ. Dietary patterns, insulin sensitivity and adiposity in the multi-ethnic Insulin Resistance Atherosclerosis Study population. Br J Nutr 2004; 96(2):973-984. and 2019³⁰30 Fröhlich C, Garcez A, Canuto R, Paniz VMV, Pattussi MP, Olinto MTA. Obesidade abdominal e padrões alimentares em mulheres trabalhadoras de turnos. Cien Saude Colet 2019; 24(9):3283-3292.

31 Holmes MD, Dalal S, Sewram V, Diamond MB, Adebamowo SN, Ajayi IO, Adebamowo C, Chiwanga FS, Njelekela M, Laurence C, Volmink J, Bajunirwe F, Nankya-Mutyoba J, Guwatudde D, Reid TG, Willett WC, Adami HO, Fung TT. Consumption of processed food dietary patterns in four African populations. Public Health Nutr 2018; 21(8):1529-1537.

32 Boggs DA, Ban Y, Palmer JR, Rosenberg L. Higher Diet Quality Is Inversely Associated with Mortality in African-American Women. J Nutr 2015; 145(3):547-554.

33 Sarfo J, Pawelzik E, Keding GB. Dietary Patterns as Characterized by Food Processing Levels and Their Association with the Health Outcomes of Rural Women in East Africa. Nutrients 2021; 13(8):2866.

34 Simonsen SE, Digre KB, Ralls B, Mukundente V, Davis FA, Rickard S, Tavake-Pasi F, Napia EE, Aiono H, Chirpich M, Stark LA, Sunada G, Keen K, Johnston L, Frost CJ, Varner MW, Alder SC. A gender-based approach to developing a healthy lifestyle and healthy weight intervention for diverse Utah women. Eval Program Plann 2015; 51:8-16.^-3535 Mukoma G, Wrottesley S V, Kagura J, Oni T, Micklesfield L, Norris SA. The relationships between socioeconomic status, dietary knowledge and patterns, and physical activity with adiposity in urban South African women. South African J Clin Nutr 2022; 36(2):56-62. and the difference between the data collection year and the publication of results varied from one³⁶36 Nettleton JA, Steffen LM, Ni H, Liu K, Jacobs DR. Dietary Patterns and Risk of Incident Type 2 Diabetes in the Multi-Ethnic Study of Atherosclerosis (MESA). Diabetes Care 2008; 31(9):1777-1782. to 13 years³⁷37 Gower BA, Pearson K, Bush N, Shikany JM, Howard VJ, Cohen CW, Tison SE, Howard G, Judd S. Diet pattern may affect fasting insulin in a large sample of black and white adults. Eur J Clin Nutr 2021; 75(4):628-635. (Chart 1).

The cross-sectional design was the most frequent one (n=13; 59.1%)⁶6 Deshmukh-Taskar PR, O'Neil CE, Nicklas TA, Yang SJ, Liu Y, Gustat J, Berenson GS. Dietary patterns associated with metabolic syndrome, sociodemographic and lifestyle factors in young adults: the Bogalusa Heart Study. Public Health Nutr 2009; 12(12):2493-2503.^,1212 Liu L, Nettleton JA, Bertoni AG, Bluemke DA, Lima JA, Szklo M. Dietary pattern, the metabolic syndrome, and left ventricular mass and systolic function: the Multi-Ethnic Study of Atherosclerosis123. Am J Clin Nutr 2009; 90(2):362-368.^,2929 Liese AD, Schulz M, Moore CG, Mayer-Davis EJ. Dietary patterns, insulin sensitivity and adiposity in the multi-ethnic Insulin Resistance Atherosclerosis Study population. Br J Nutr 2004; 96(2):973-984.^,3131 Holmes MD, Dalal S, Sewram V, Diamond MB, Adebamowo SN, Ajayi IO, Adebamowo C, Chiwanga FS, Njelekela M, Laurence C, Volmink J, Bajunirwe F, Nankya-Mutyoba J, Guwatudde D, Reid TG, Willett WC, Adami HO, Fung TT. Consumption of processed food dietary patterns in four African populations. Public Health Nutr 2018; 21(8):1529-1537.^,3333 Sarfo J, Pawelzik E, Keding GB. Dietary Patterns as Characterized by Food Processing Levels and Their Association with the Health Outcomes of Rural Women in East Africa. Nutrients 2021; 13(8):2866.^,3535 Mukoma G, Wrottesley S V, Kagura J, Oni T, Micklesfield L, Norris SA. The relationships between socioeconomic status, dietary knowledge and patterns, and physical activity with adiposity in urban South African women. South African J Clin Nutr 2022; 36(2):56-62.^,3838 Liu J, Hickson DA, Musani SK, Talegawkar SA, Carithers TC, Tucker KL, Fox CS, Taylor HA. Dietary patterns, abdominal visceral adipose tissue, and cardiometabolic risk factors in African Americans: the Jackson heart study. Obesity 2013; 21(3):644-651.

39 Perozzo G, Olinto MT, Dias-da-Costa JS, Henn RL, Sarriera J, Pattussi MP. Associação dos padrões alimentares com obesidade geral e abdominal em mulheres residentes no Sul do Brasil. Cad Saude Publica 2008; 24(10):2427-2439.

40 Nettleton JA, Steffen LM, Mayer-Davis EJ, Jenny NS, Jiang R, Herrington DM, Jacobs DR. Dietary patterns are associated with biochemical markers of inflammation and endothelial activation in the Multi-Ethnic Study of Atherosclerosis (MESA). Am J Clin Nutr 2006; 83(6):1369-1379.

41 Delisle HF, Vioque J, Gil A. Dietary patterns and quality in West-African immigrants in Madrid. Nutr J 2009; 8:3.

42 Silva BDP, Neutzling MB, Camey S, Olinto MT. Dietary patterns and hypertension: a population-based study with women from Southern Brazil. Cad Saude Publica 2014; 30(5):961-971.

43 Becquey E, Savy M, Danel P, Dabiré HB, Tapsoba S, Martin-Prével Y. Dietary patterns of adults living in Ouagadougou and their association with overweight. Nutr J 2010; 9:13.^-4444 Davis NJ, Schechter CB, Ortega F, Rosen R, Wylie-Rosett J, Walker EA. Dietary patterns in blacks and Hispanics with diagnosed diabetes in New York City's South Bronx. Am J Clin Nutr 2013; 97(4):878-885. and only eight studies included only women in their samples³⁰30 Fröhlich C, Garcez A, Canuto R, Paniz VMV, Pattussi MP, Olinto MTA. Obesidade abdominal e padrões alimentares em mulheres trabalhadoras de turnos. Cien Saude Colet 2019; 24(9):3283-3292.^,3232 Boggs DA, Ban Y, Palmer JR, Rosenberg L. Higher Diet Quality Is Inversely Associated with Mortality in African-American Women. J Nutr 2015; 145(3):547-554.^,3333 Sarfo J, Pawelzik E, Keding GB. Dietary Patterns as Characterized by Food Processing Levels and Their Association with the Health Outcomes of Rural Women in East Africa. Nutrients 2021; 13(8):2866.^,3535 Mukoma G, Wrottesley S V, Kagura J, Oni T, Micklesfield L, Norris SA. The relationships between socioeconomic status, dietary knowledge and patterns, and physical activity with adiposity in urban South African women. South African J Clin Nutr 2022; 36(2):56-62.^,3939 Perozzo G, Olinto MT, Dias-da-Costa JS, Henn RL, Sarriera J, Pattussi MP. Associação dos padrões alimentares com obesidade geral e abdominal em mulheres residentes no Sul do Brasil. Cad Saude Publica 2008; 24(10):2427-2439.^,4242 Silva BDP, Neutzling MB, Camey S, Olinto MT. Dietary patterns and hypertension: a population-based study with women from Southern Brazil. Cad Saude Publica 2014; 30(5):961-971.^,4545 Boggs DA, Palmer JR, Spiegelman D, Stampfer MJ, Adams-Campbell LL, Rosenberg L. Dietary patterns and 14-y weight gain in African American women. Am J Clin Nutr 2011; 94(1):86-94.^,4646 Keding GB, Msuya JM, Maass BL, Krawinkel MB. Dietary patterns and nutritional health of women: the nutrition transition in rural Tanzania. Food Nutr Bull 2011; 32(3):218-226.. Amongst the other research that assessed both genders, the percentage contribution of women to the samples ranged from 47%³⁶36 Nettleton JA, Steffen LM, Ni H, Liu K, Jacobs DR. Dietary Patterns and Risk of Incident Type 2 Diabetes in the Multi-Ethnic Study of Atherosclerosis (MESA). Diabetes Care 2008; 31(9):1777-1782. to 76%⁴⁷47 Frank LK, Kröger J, Schulze MB, Bedu-Addo G, Mockenhaupt FP, Danquah I. Dietary patterns in urban Ghana and risk of type 2 diabetes. Br J Nutr 2014; 112(1):89-98. (Chart 1). Of these, only four presented data on food consumption stratified by gender³¹31 Holmes MD, Dalal S, Sewram V, Diamond MB, Adebamowo SN, Ajayi IO, Adebamowo C, Chiwanga FS, Njelekela M, Laurence C, Volmink J, Bajunirwe F, Nankya-Mutyoba J, Guwatudde D, Reid TG, Willett WC, Adami HO, Fung TT. Consumption of processed food dietary patterns in four African populations. Public Health Nutr 2018; 21(8):1529-1537.^,3232 Boggs DA, Ban Y, Palmer JR, Rosenberg L. Higher Diet Quality Is Inversely Associated with Mortality in African-American Women. J Nutr 2015; 145(3):547-554.^,4848 Nettleton JA, Polak JF, Tracy R, Burke GL, Jacobs DR. Dietary patterns and incident cardiovascular disease in the Multi-Ethnic Study of Atherosclerosis. Am J Clin Nutr 2009; 90(3):647-654.^,4949 Lara KM, Levitan EB, Gutierrez OM, Shikany JM, Safford MM, Judd SE, Rosenson RS. Dietary Patterns and Incident Heart Failure in U.S. Adults Without Known Coronary Disease. J Am Coll Cardiol 2019; 73(16):2036-2045..

Regarding ethnicity, 10 studies (45.4%) were carried out only on Afro-descendant population³¹31 Holmes MD, Dalal S, Sewram V, Diamond MB, Adebamowo SN, Ajayi IO, Adebamowo C, Chiwanga FS, Njelekela M, Laurence C, Volmink J, Bajunirwe F, Nankya-Mutyoba J, Guwatudde D, Reid TG, Willett WC, Adami HO, Fung TT. Consumption of processed food dietary patterns in four African populations. Public Health Nutr 2018; 21(8):1529-1537.

32 Boggs DA, Ban Y, Palmer JR, Rosenberg L. Higher Diet Quality Is Inversely Associated with Mortality in African-American Women. J Nutr 2015; 145(3):547-554.^-3333 Sarfo J, Pawelzik E, Keding GB. Dietary Patterns as Characterized by Food Processing Levels and Their Association with the Health Outcomes of Rural Women in East Africa. Nutrients 2021; 13(8):2866.^,3535 Mukoma G, Wrottesley S V, Kagura J, Oni T, Micklesfield L, Norris SA. The relationships between socioeconomic status, dietary knowledge and patterns, and physical activity with adiposity in urban South African women. South African J Clin Nutr 2022; 36(2):56-62.^,3838 Liu J, Hickson DA, Musani SK, Talegawkar SA, Carithers TC, Tucker KL, Fox CS, Taylor HA. Dietary patterns, abdominal visceral adipose tissue, and cardiometabolic risk factors in African Americans: the Jackson heart study. Obesity 2013; 21(3):644-651.^,4141 Delisle HF, Vioque J, Gil A. Dietary patterns and quality in West-African immigrants in Madrid. Nutr J 2009; 8:3.^,4343 Becquey E, Savy M, Danel P, Dabiré HB, Tapsoba S, Martin-Prével Y. Dietary patterns of adults living in Ouagadougou and their association with overweight. Nutr J 2010; 9:13.^,4545 Boggs DA, Palmer JR, Spiegelman D, Stampfer MJ, Adams-Campbell LL, Rosenberg L. Dietary patterns and 14-y weight gain in African American women. Am J Clin Nutr 2011; 94(1):86-94.

46 Keding GB, Msuya JM, Maass BL, Krawinkel MB. Dietary patterns and nutritional health of women: the nutrition transition in rural Tanzania. Food Nutr Bull 2011; 32(3):218-226.^-4747 Frank LK, Kröger J, Schulze MB, Bedu-Addo G, Mockenhaupt FP, Danquah I. Dietary patterns in urban Ghana and risk of type 2 diabetes. Br J Nutr 2014; 112(1):89-98. (Chart 1).

All studies analyzed at least one risk factor for MetS or this condition itself. The conditions most frequently studied were DM and factors related to it (n=5)²⁹29 Liese AD, Schulz M, Moore CG, Mayer-Davis EJ. Dietary patterns, insulin sensitivity and adiposity in the multi-ethnic Insulin Resistance Atherosclerosis Study population. Br J Nutr 2004; 96(2):973-984.^,3636 Nettleton JA, Steffen LM, Ni H, Liu K, Jacobs DR. Dietary Patterns and Risk of Incident Type 2 Diabetes in the Multi-Ethnic Study of Atherosclerosis (MESA). Diabetes Care 2008; 31(9):1777-1782.^,3737 Gower BA, Pearson K, Bush N, Shikany JM, Howard VJ, Cohen CW, Tison SE, Howard G, Judd S. Diet pattern may affect fasting insulin in a large sample of black and white adults. Eur J Clin Nutr 2021; 75(4):628-635.^,4444 Davis NJ, Schechter CB, Ortega F, Rosen R, Wylie-Rosett J, Walker EA. Dietary patterns in blacks and Hispanics with diagnosed diabetes in New York City's South Bronx. Am J Clin Nutr 2013; 97(4):878-885.^,4747 Frank LK, Kröger J, Schulze MB, Bedu-Addo G, Mockenhaupt FP, Danquah I. Dietary patterns in urban Ghana and risk of type 2 diabetes. Br J Nutr 2014; 112(1):89-98.; obesity/overweight and abdominal obesity (n=9)³⁰30 Fröhlich C, Garcez A, Canuto R, Paniz VMV, Pattussi MP, Olinto MTA. Obesidade abdominal e padrões alimentares em mulheres trabalhadoras de turnos. Cien Saude Colet 2019; 24(9):3283-3292.

31 Holmes MD, Dalal S, Sewram V, Diamond MB, Adebamowo SN, Ajayi IO, Adebamowo C, Chiwanga FS, Njelekela M, Laurence C, Volmink J, Bajunirwe F, Nankya-Mutyoba J, Guwatudde D, Reid TG, Willett WC, Adami HO, Fung TT. Consumption of processed food dietary patterns in four African populations. Public Health Nutr 2018; 21(8):1529-1537.

32 Boggs DA, Ban Y, Palmer JR, Rosenberg L. Higher Diet Quality Is Inversely Associated with Mortality in African-American Women. J Nutr 2015; 145(3):547-554.^-3333 Sarfo J, Pawelzik E, Keding GB. Dietary Patterns as Characterized by Food Processing Levels and Their Association with the Health Outcomes of Rural Women in East Africa. Nutrients 2021; 13(8):2866.^,3535 Mukoma G, Wrottesley S V, Kagura J, Oni T, Micklesfield L, Norris SA. The relationships between socioeconomic status, dietary knowledge and patterns, and physical activity with adiposity in urban South African women. South African J Clin Nutr 2022; 36(2):56-62.^,3939 Perozzo G, Olinto MT, Dias-da-Costa JS, Henn RL, Sarriera J, Pattussi MP. Associação dos padrões alimentares com obesidade geral e abdominal em mulheres residentes no Sul do Brasil. Cad Saude Publica 2008; 24(10):2427-2439.^,4343 Becquey E, Savy M, Danel P, Dabiré HB, Tapsoba S, Martin-Prével Y. Dietary patterns of adults living in Ouagadougou and their association with overweight. Nutr J 2010; 9:13.^,4545 Boggs DA, Palmer JR, Spiegelman D, Stampfer MJ, Adams-Campbell LL, Rosenberg L. Dietary patterns and 14-y weight gain in African American women. Am J Clin Nutr 2011; 94(1):86-94.^,4646 Keding GB, Msuya JM, Maass BL, Krawinkel MB. Dietary patterns and nutritional health of women: the nutrition transition in rural Tanzania. Food Nutr Bull 2011; 32(3):218-226. and MetS (n=3)⁶6 Deshmukh-Taskar PR, O'Neil CE, Nicklas TA, Yang SJ, Liu Y, Gustat J, Berenson GS. Dietary patterns associated with metabolic syndrome, sociodemographic and lifestyle factors in young adults: the Bogalusa Heart Study. Public Health Nutr 2009; 12(12):2493-2503.^,1212 Liu L, Nettleton JA, Bertoni AG, Bluemke DA, Lima JA, Szklo M. Dietary pattern, the metabolic syndrome, and left ventricular mass and systolic function: the Multi-Ethnic Study of Atherosclerosis123. Am J Clin Nutr 2009; 90(2):362-368.^,3838 Liu J, Hickson DA, Musani SK, Talegawkar SA, Carithers TC, Tucker KL, Fox CS, Taylor HA. Dietary patterns, abdominal visceral adipose tissue, and cardiometabolic risk factors in African Americans: the Jackson heart study. Obesity 2013; 21(3):644-651. (Chart 1).

Almost all studies (n=19) used only the food frequency questionnaire (FFQ) as an assessment method of food consumption⁶6 Deshmukh-Taskar PR, O'Neil CE, Nicklas TA, Yang SJ, Liu Y, Gustat J, Berenson GS. Dietary patterns associated with metabolic syndrome, sociodemographic and lifestyle factors in young adults: the Bogalusa Heart Study. Public Health Nutr 2009; 12(12):2493-2503.^,1212 Liu L, Nettleton JA, Bertoni AG, Bluemke DA, Lima JA, Szklo M. Dietary pattern, the metabolic syndrome, and left ventricular mass and systolic function: the Multi-Ethnic Study of Atherosclerosis123. Am J Clin Nutr 2009; 90(2):362-368.^,2929 Liese AD, Schulz M, Moore CG, Mayer-Davis EJ. Dietary patterns, insulin sensitivity and adiposity in the multi-ethnic Insulin Resistance Atherosclerosis Study population. Br J Nutr 2004; 96(2):973-984.

30 Fröhlich C, Garcez A, Canuto R, Paniz VMV, Pattussi MP, Olinto MTA. Obesidade abdominal e padrões alimentares em mulheres trabalhadoras de turnos. Cien Saude Colet 2019; 24(9):3283-3292.

31 Holmes MD, Dalal S, Sewram V, Diamond MB, Adebamowo SN, Ajayi IO, Adebamowo C, Chiwanga FS, Njelekela M, Laurence C, Volmink J, Bajunirwe F, Nankya-Mutyoba J, Guwatudde D, Reid TG, Willett WC, Adami HO, Fung TT. Consumption of processed food dietary patterns in four African populations. Public Health Nutr 2018; 21(8):1529-1537.

32 Boggs DA, Ban Y, Palmer JR, Rosenberg L. Higher Diet Quality Is Inversely Associated with Mortality in African-American Women. J Nutr 2015; 145(3):547-554.^-3333 Sarfo J, Pawelzik E, Keding GB. Dietary Patterns as Characterized by Food Processing Levels and Their Association with the Health Outcomes of Rural Women in East Africa. Nutrients 2021; 13(8):2866.^,3535 Mukoma G, Wrottesley S V, Kagura J, Oni T, Micklesfield L, Norris SA. The relationships between socioeconomic status, dietary knowledge and patterns, and physical activity with adiposity in urban South African women. South African J Clin Nutr 2022; 36(2):56-62.

36 Nettleton JA, Steffen LM, Ni H, Liu K, Jacobs DR. Dietary Patterns and Risk of Incident Type 2 Diabetes in the Multi-Ethnic Study of Atherosclerosis (MESA). Diabetes Care 2008; 31(9):1777-1782.

37 Gower BA, Pearson K, Bush N, Shikany JM, Howard VJ, Cohen CW, Tison SE, Howard G, Judd S. Diet pattern may affect fasting insulin in a large sample of black and white adults. Eur J Clin Nutr 2021; 75(4):628-635.

38 Liu J, Hickson DA, Musani SK, Talegawkar SA, Carithers TC, Tucker KL, Fox CS, Taylor HA. Dietary patterns, abdominal visceral adipose tissue, and cardiometabolic risk factors in African Americans: the Jackson heart study. Obesity 2013; 21(3):644-651.

39 Perozzo G, Olinto MT, Dias-da-Costa JS, Henn RL, Sarriera J, Pattussi MP. Associação dos padrões alimentares com obesidade geral e abdominal em mulheres residentes no Sul do Brasil. Cad Saude Publica 2008; 24(10):2427-2439.

40 Nettleton JA, Steffen LM, Mayer-Davis EJ, Jenny NS, Jiang R, Herrington DM, Jacobs DR. Dietary patterns are associated with biochemical markers of inflammation and endothelial activation in the Multi-Ethnic Study of Atherosclerosis (MESA). Am J Clin Nutr 2006; 83(6):1369-1379.

41 Delisle HF, Vioque J, Gil A. Dietary patterns and quality in West-African immigrants in Madrid. Nutr J 2009; 8:3.

42 Silva BDP, Neutzling MB, Camey S, Olinto MT. Dietary patterns and hypertension: a population-based study with women from Southern Brazil. Cad Saude Publica 2014; 30(5):961-971.

43 Becquey E, Savy M, Danel P, Dabiré HB, Tapsoba S, Martin-Prével Y. Dietary patterns of adults living in Ouagadougou and their association with overweight. Nutr J 2010; 9:13.

44 Davis NJ, Schechter CB, Ortega F, Rosen R, Wylie-Rosett J, Walker EA. Dietary patterns in blacks and Hispanics with diagnosed diabetes in New York City's South Bronx. Am J Clin Nutr 2013; 97(4):878-885.^-4545 Boggs DA, Palmer JR, Spiegelman D, Stampfer MJ, Adams-Campbell LL, Rosenberg L. Dietary patterns and 14-y weight gain in African American women. Am J Clin Nutr 2011; 94(1):86-94.^,4848 Nettleton JA, Polak JF, Tracy R, Burke GL, Jacobs DR. Dietary patterns and incident cardiovascular disease in the Multi-Ethnic Study of Atherosclerosis. Am J Clin Nutr 2009; 90(3):647-654.^,4949 Lara KM, Levitan EB, Gutierrez OM, Shikany JM, Safford MM, Judd SE, Rosenson RS. Dietary Patterns and Incident Heart Failure in U.S. Adults Without Known Coronary Disease. J Am Coll Cardiol 2019; 73(16):2036-2045. (Chart 2).

As to the definition of dietary patterns, 18 studies derived the dietary patterns through the PCA or FA methods⁶6 Deshmukh-Taskar PR, O'Neil CE, Nicklas TA, Yang SJ, Liu Y, Gustat J, Berenson GS. Dietary patterns associated with metabolic syndrome, sociodemographic and lifestyle factors in young adults: the Bogalusa Heart Study. Public Health Nutr 2009; 12(12):2493-2503.^,1212 Liu L, Nettleton JA, Bertoni AG, Bluemke DA, Lima JA, Szklo M. Dietary pattern, the metabolic syndrome, and left ventricular mass and systolic function: the Multi-Ethnic Study of Atherosclerosis123. Am J Clin Nutr 2009; 90(2):362-368.^,3030 Fröhlich C, Garcez A, Canuto R, Paniz VMV, Pattussi MP, Olinto MTA. Obesidade abdominal e padrões alimentares em mulheres trabalhadoras de turnos. Cien Saude Colet 2019; 24(9):3283-3292.

31 Holmes MD, Dalal S, Sewram V, Diamond MB, Adebamowo SN, Ajayi IO, Adebamowo C, Chiwanga FS, Njelekela M, Laurence C, Volmink J, Bajunirwe F, Nankya-Mutyoba J, Guwatudde D, Reid TG, Willett WC, Adami HO, Fung TT. Consumption of processed food dietary patterns in four African populations. Public Health Nutr 2018; 21(8):1529-1537.

32 Boggs DA, Ban Y, Palmer JR, Rosenberg L. Higher Diet Quality Is Inversely Associated with Mortality in African-American Women. J Nutr 2015; 145(3):547-554.^-3333 Sarfo J, Pawelzik E, Keding GB. Dietary Patterns as Characterized by Food Processing Levels and Their Association with the Health Outcomes of Rural Women in East Africa. Nutrients 2021; 13(8):2866.^,3535 Mukoma G, Wrottesley S V, Kagura J, Oni T, Micklesfield L, Norris SA. The relationships between socioeconomic status, dietary knowledge and patterns, and physical activity with adiposity in urban South African women. South African J Clin Nutr 2022; 36(2):56-62.

36 Nettleton JA, Steffen LM, Ni H, Liu K, Jacobs DR. Dietary Patterns and Risk of Incident Type 2 Diabetes in the Multi-Ethnic Study of Atherosclerosis (MESA). Diabetes Care 2008; 31(9):1777-1782.^-3737 Gower BA, Pearson K, Bush N, Shikany JM, Howard VJ, Cohen CW, Tison SE, Howard G, Judd S. Diet pattern may affect fasting insulin in a large sample of black and white adults. Eur J Clin Nutr 2021; 75(4):628-635.^,3939 Perozzo G, Olinto MT, Dias-da-Costa JS, Henn RL, Sarriera J, Pattussi MP. Associação dos padrões alimentares com obesidade geral e abdominal em mulheres residentes no Sul do Brasil. Cad Saude Publica 2008; 24(10):2427-2439.^,4040 Nettleton JA, Steffen LM, Mayer-Davis EJ, Jenny NS, Jiang R, Herrington DM, Jacobs DR. Dietary patterns are associated with biochemical markers of inflammation and endothelial activation in the Multi-Ethnic Study of Atherosclerosis (MESA). Am J Clin Nutr 2006; 83(6):1369-1379.^,4343 Becquey E, Savy M, Danel P, Dabiré HB, Tapsoba S, Martin-Prével Y. Dietary patterns of adults living in Ouagadougou and their association with overweight. Nutr J 2010; 9:13.

44 Davis NJ, Schechter CB, Ortega F, Rosen R, Wylie-Rosett J, Walker EA. Dietary patterns in blacks and Hispanics with diagnosed diabetes in New York City's South Bronx. Am J Clin Nutr 2013; 97(4):878-885.

45 Boggs DA, Palmer JR, Spiegelman D, Stampfer MJ, Adams-Campbell LL, Rosenberg L. Dietary patterns and 14-y weight gain in African American women. Am J Clin Nutr 2011; 94(1):86-94.

46 Keding GB, Msuya JM, Maass BL, Krawinkel MB. Dietary patterns and nutritional health of women: the nutrition transition in rural Tanzania. Food Nutr Bull 2011; 32(3):218-226.

47 Frank LK, Kröger J, Schulze MB, Bedu-Addo G, Mockenhaupt FP, Danquah I. Dietary patterns in urban Ghana and risk of type 2 diabetes. Br J Nutr 2014; 112(1):89-98.

48 Nettleton JA, Polak JF, Tracy R, Burke GL, Jacobs DR. Dietary patterns and incident cardiovascular disease in the Multi-Ethnic Study of Atherosclerosis. Am J Clin Nutr 2009; 90(3):647-654.^-4949 Lara KM, Levitan EB, Gutierrez OM, Shikany JM, Safford MM, Judd SE, Rosenson RS. Dietary Patterns and Incident Heart Failure in U.S. Adults Without Known Coronary Disease. J Am Coll Cardiol 2019; 73(16):2036-2045. and the number of patterns established in each study ranged from two to six. Seven studies⁶6 Deshmukh-Taskar PR, O'Neil CE, Nicklas TA, Yang SJ, Liu Y, Gustat J, Berenson GS. Dietary patterns associated with metabolic syndrome, sociodemographic and lifestyle factors in young adults: the Bogalusa Heart Study. Public Health Nutr 2009; 12(12):2493-2503.^,3131 Holmes MD, Dalal S, Sewram V, Diamond MB, Adebamowo SN, Ajayi IO, Adebamowo C, Chiwanga FS, Njelekela M, Laurence C, Volmink J, Bajunirwe F, Nankya-Mutyoba J, Guwatudde D, Reid TG, Willett WC, Adami HO, Fung TT. Consumption of processed food dietary patterns in four African populations. Public Health Nutr 2018; 21(8):1529-1537.^,3232 Boggs DA, Ban Y, Palmer JR, Rosenberg L. Higher Diet Quality Is Inversely Associated with Mortality in African-American Women. J Nutr 2015; 145(3):547-554.^,4141 Delisle HF, Vioque J, Gil A. Dietary patterns and quality in West-African immigrants in Madrid. Nutr J 2009; 8:3.^,4343 Becquey E, Savy M, Danel P, Dabiré HB, Tapsoba S, Martin-Prével Y. Dietary patterns of adults living in Ouagadougou and their association with overweight. Nutr J 2010; 9:13.^,4545 Boggs DA, Palmer JR, Spiegelman D, Stampfer MJ, Adams-Campbell LL, Rosenberg L. Dietary patterns and 14-y weight gain in African American women. Am J Clin Nutr 2011; 94(1):86-94.^,4747 Frank LK, Kröger J, Schulze MB, Bedu-Addo G, Mockenhaupt FP, Danquah I. Dietary patterns in urban Ghana and risk of type 2 diabetes. Br J Nutr 2014; 112(1):89-98. assessed the association of the outcome with two distinct dietary patterns and only one assessed six distinct dietary patterns²⁹29 Liese AD, Schulz M, Moore CG, Mayer-Davis EJ. Dietary patterns, insulin sensitivity and adiposity in the multi-ethnic Insulin Resistance Atherosclerosis Study population. Br J Nutr 2004; 96(2):973-984. (Chart 2).

The healthy dietary pattern included in the MA was characterized by the presence of the following food groups: vegetables, whole grains, low-fat dairy products, legumes, soup, fish, nuts, and oils (olive oil and other vegetable oils). The food groups included in the unhealthy dietary pattern were sauces, eggs (without specification of cooking method and based on the recommendations of a food pattern with characteristics of the Mediterranean diet) tomato sauce, pasta, ready-made salad dressing, refined grains, fries, high-fat dairy products, red meat, processed meat, sweets and desserts, sugar-sweetened drinks, condiments, margarine, canned fish, coffee, fried food, and fast food. It is important to highlight that each study named the dietary patterns distinctively (Chart 2).

The methodological quality of the articles was classified as strong for 14 studies, moderate for six, and weak for two works (Chart 1).

Dietary pattern MA and its association with MetS or its risk factors

Healthy dietary pattern

Eleven studies met the MA inclusion criteria. Four articles were analyzed as to the healthy dietary pattern in the Women Population group, not evidencing the relation with the occurrence of MetS-RF (Figure 2.1 A). In the Afro-descendant Population group (5 studies), results were like those of the Women Population (Figure 2.1 B). As to the General Population (9 research), in contrast to the other two groups, there was a significant association (OR=0.77; 95%CI: 0.61-0.98), despite the high (I²=79%) heterogeneity (Figure 2.1 C).

In the analysis of sub-groups (data not shown), regardless of gender or ethnicity, the stratification by study design pointed out reduced the chance for MetS-RF in cohort studies (n=4), being observed absence of heterogeneity (I²=0%). The stratification by study conduction location pointed out that the healthy pattern reduced the chance of outcomes for studies conducted in the USA, although with elevated heterogeneity (I²=74%). The studies with women percentage >50% in their samples denoted also that the healthy pattern did not lead to a decreased chance for the development of MetS risk factors. In the studies with a percentage sample lower than 50% of Afro-descendant individuals, the healthy dietary pattern reduced the chance for MetS-RF (OR=0.75; 95%CI: 0.57-0.98), although with high heterogeneity (I²=83%). In the sensitivity analysis, the single exclusion of one of the studies did not reduce heterogeneity, however, the exclusion of two studies ⁶6 Deshmukh-Taskar PR, O'Neil CE, Nicklas TA, Yang SJ, Liu Y, Gustat J, Berenson GS. Dietary patterns associated with metabolic syndrome, sociodemographic and lifestyle factors in young adults: the Bogalusa Heart Study. Public Health Nutr 2009; 12(12):2493-2503.^,3030 Fröhlich C, Garcez A, Canuto R, Paniz VMV, Pattussi MP, Olinto MTA. Obesidade abdominal e padrões alimentares em mulheres trabalhadoras de turnos. Cien Saude Colet 2019; 24(9):3283-3292. caused more homogeneous results (OR=0,62; 95%CI: 0.55-0.71; I²=0%).

The funnel plots of the MA on healthy dietary patterns presented asymmetry (Figure 3), revealing possible publication bias.

Unhealthy dietary pattern

Seven studies were included in the assessment of unhealthy dietary patterns for the Women Population, to which the results of the MA (OR=1.61; 95%CI: 1.35-1.91; I²=14%) evidenced that greater consumption of food of such pattern increases the odds for MetS-RF (Figure 2.2 A). For the Afro-descendant Population (Figure 2.2 B), by the analysis of six studies, the unhealthy dietary pattern also indicated a greater risk for MetS-RF (OR=1.64; 95%CI: 1.15-2.32; I²=71%).

Eleven studies were included in the MA on the unhealthy dietary pattern for the General Population. Grouped OR to different outcomes related to MetS in the comparison of the highest category about the lowest category of food consumption of unhealthy dietary patterns (Figure 2.2 C) was 1.31 (95%CI: 1.14-1.52; I²=78%). In the sensitivity analysis, the exclusion of any one of the studies continued indicating that the unhealthy pattern was associated with higher odds for MetS-RF while keeping high heterogeneity (data not shown).

In the Analysis of sub-groups (data not shown), it was verified that the results involving cohort studies presented moderate heterogeneity (I²=40%); the unhealthy dietary pattern did not increase the odds for the development of MetS-RF in the studies carried out outside the USA; a greater presence of Afro-descendant individuals in the samples elevated heterogeneity to 80%.

The funnel plots of the MA in the unhealthy dietary pattern presented asymmetry (Figure 3 B), suggesting the presence of publication bias.

Evidence quality

NutriGrade scoring obtained by the studies of the healthy dietary pattern was 3.75 for the MA involving Women and Afro-descendant Populations, indicating Very Low evidence quality. As to the metanalysis involving the General Population, the scoring was 7.05, indicating moderate evidence strength. In the MA for unhealthy dietary patterns, the scorings were: 6.15 for the Women Population; 6.05 for the Afro-descendant Population, and 6.35 for the General Population. All these scorings indicate moderate evidence quality. The main reasons that contributed to the observed decreased scorings were “precision”, “heterogeneity”, “dose-response” and “effect size”, in addition to the presence of “publication bias”.

Discussion

In this SR, the relation between “healthy” and “unhealthy” dietary patterns, and the MetS-RF was analyzed. The healthy eating pattern reduced the chances for such outcomes when the results obtained in the articles included individuals classified here as the General Population in their samples.

Regarding “unhealthy” dietary patterns, it was observed greater odds for the development of MetS-RF in the aggregated analysis involving all groups, regardless of the population involved.

In the studies related to the General Population, it was observed that the healthy pattern reduced in 13% the odds ratio for the development of MetS-RF. Such effect can be in part attributed to the characteristics of food consumption observed in this type of pattern, with high intake of whole grains, fruit and vegetables, low-fat dairy products, foods rich in polyunsaturated fatty acids (which are related to multiple benefic effects to health⁵⁰50 Newby PK, Tucker KL. Empirically derived eating patterns using factor or cluster analysis: a review. Nutr Rev 2004; 62(5):177-203.), and, in parallel, low intake of red or processed meat, refined grains and processed snack food⁶6 Deshmukh-Taskar PR, O'Neil CE, Nicklas TA, Yang SJ, Liu Y, Gustat J, Berenson GS. Dietary patterns associated with metabolic syndrome, sociodemographic and lifestyle factors in young adults: the Bogalusa Heart Study. Public Health Nutr 2009; 12(12):2493-2503.^,3737 Gower BA, Pearson K, Bush N, Shikany JM, Howard VJ, Cohen CW, Tison SE, Howard G, Judd S. Diet pattern may affect fasting insulin in a large sample of black and white adults. Eur J Clin Nutr 2021; 75(4):628-635.^,3939 Perozzo G, Olinto MT, Dias-da-Costa JS, Henn RL, Sarriera J, Pattussi MP. Associação dos padrões alimentares com obesidade geral e abdominal em mulheres residentes no Sul do Brasil. Cad Saude Publica 2008; 24(10):2427-2439.^,4848 Nettleton JA, Polak JF, Tracy R, Burke GL, Jacobs DR. Dietary patterns and incident cardiovascular disease in the Multi-Ethnic Study of Atherosclerosis. Am J Clin Nutr 2009; 90(3):647-654.^,4949 Lara KM, Levitan EB, Gutierrez OM, Shikany JM, Safford MM, Judd SE, Rosenson RS. Dietary Patterns and Incident Heart Failure in U.S. Adults Without Known Coronary Disease. J Am Coll Cardiol 2019; 73(16):2036-2045.. These results corroborate those of other SR⁵5 Rodríguez-Monforte M, Sánchez E, Barrio F, Costa B, Flores-Mateo G. Metabolic syndrome and dietary patterns: a systematic review and meta-analysis of observational studies. Eur J Nutr 2017; 56(3):925-947.^,88 Fabiani R, Naldini G, Chiavarini M. Dietary Patterns and Metabolic Syndrome in Adult Subjects: A Systematic Review and Meta-Analysis. Nutrients 2019; 11(9):2056..

The healthy dietary pattern was not associated with MetS-RF in the studies that involved the Women Population or the Afro-descendant Population. One possible explanation would be the scarcity of studies with this approach. Other SR-MA studies that did not analyze the ethnicity issue, here classified in the General Population, verified the protective effect of healthy dietary patterns for MetS⁵5 Rodríguez-Monforte M, Sánchez E, Barrio F, Costa B, Flores-Mateo G. Metabolic syndrome and dietary patterns: a systematic review and meta-analysis of observational studies. Eur J Nutr 2017; 56(3):925-947.^,88 Fabiani R, Naldini G, Chiavarini M. Dietary Patterns and Metabolic Syndrome in Adult Subjects: A Systematic Review and Meta-Analysis. Nutrients 2019; 11(9):2056.^,5151 Shab-Bidar S, Golzarand M, Hajimohammadi M, Mansouri S. A posteriori dietary patterns and metabolic syndrome in adults: a systematic review and meta-analysis of observational studies. Public Health Nutr 2018; 21(9):1681-1692.. These studies were carried out with the inclusion of a greater quantity of publications (19 to 38), conferring them greater statistical power.

It is important to highlight that the different studies included in this SR-MA addressed different outcomes. Because there wasn’t sufficient information in the primary studies to conduct a stratified analysis, all the data was analyzed in aggregate, with the MetS-RF as the outcome of interest. Furthermore, most studies used food frequency questionnaires to gather information on dietary patterns, which is a tool that’s more susceptible to memory bias and overestimation of healthy food consumption⁵²52 Aljefree N, Ahmed F. Association between dietary pattern and risk of cardiovascular disease among adults in the Middle East and North Africa region: a systematic review. Food Nutr Res 2015; 59(1):27486..

When studying the effects of dietary patterns on health, it’s important to consider how the results are categorized (tertile, quartile, or quintile) when comparing lower versus higher consumption. An MA examining the link between ultra-processed food consumption and the risk of noncommunicable diseases⁵³53 Lane MM, Davis JA, Beattie S, Gómez-Donoso C, Loughman A, O'Neil A, Jacka F, Berk M, Page R, Marx W, Rocks T. Ultraprocessed food and chronic noncommunicable diseases: A systematic review and meta-analysis of 43 observational studies. Obes Rev 2021; 22(3):e13146 found discrepancies in these categorizations, which can limit the conclusions drawn from the findings. To address this, the study recommends using standardized approaches to define the categories being compared. Additionally, factors such as geographic location and population characteristics should be considered, as they can explain much of the variability in results.

In the present MA, the studies with unhealthy patterns indicated an increment in the odds for MetS, being 31% for the General Population, 61% for the Afro-descendant Population, and 64% for the Women Population. These patterns are characterized by the presence of red meat, processed and ultra-processed food with high energy density, high content of saturated fats and trans fats, poor fibers, and micronutrients. Several biological mechanisms have been pointed out to explain the possible deleterious effects on health-related to unhealthy patterns. Among these, it is mentioned that foods that are sources of refined carbohydrates, red and processed/ultra-processed meat, fast food in general, and fried food have pro-inflammation properties, enabling the increased presence of certain cytokines that would be involved in the genesis of several chronic diseases⁷7 Godos J, Bella F, Torrisi A, Sciacca S, Galvano F, Grosso G. Dietary patterns and risk of colorectal adenoma: a systematic review and meta-analysis of observational studies. J Hum Nutr Diet 2016; 29(6):757-767.^,5454 Deng FE, Shivappa N, Tang Y, Mann JR, Hebert JR. Association between diet-related inflammation, all-cause, all-cancer, and cardiovascular disease mortality, with special focus on prediabetics: findings from NHANES III. Eur J Nutr 2017; 56(3):1085-1093..

Some studies have revealed that the consumption of foods with high energy density, high content of fats, and reduced fiber supply is related to a lower sensitivity to insulin and greater risk for the development of type 2 diabetes⁵⁵55 McNaughton SA, Mishra GD, Brunner EJ. Dietary Patterns, Insulin Resistance, and Incidence of Type 2 Diabetes in the Whitehall II Study. Diabetes Care 2008; 31(7):1343-1348., accumulation of visceral fat⁵⁶56 Votruba SB, Mattison RS, Dumesic DA, Koutsari C, Jensen MD. Meal Fatty Acid Uptake in Visceral Fat in Women. Diabetes 2007; 56(10):2589-2597., increased plasma lipids, MetS⁶6 Deshmukh-Taskar PR, O'Neil CE, Nicklas TA, Yang SJ, Liu Y, Gustat J, Berenson GS. Dietary patterns associated with metabolic syndrome, sociodemographic and lifestyle factors in young adults: the Bogalusa Heart Study. Public Health Nutr 2009; 12(12):2493-2503.^,1212 Liu L, Nettleton JA, Bertoni AG, Bluemke DA, Lima JA, Szklo M. Dietary pattern, the metabolic syndrome, and left ventricular mass and systolic function: the Multi-Ethnic Study of Atherosclerosis123. Am J Clin Nutr 2009; 90(2):362-368., and increased presence of inflammatory cytokines⁵⁷57 Lopez-Garcia E, Schulze MB, Fung TT, Meigs JB, Rifai N, Manson JE, Hu FB. Major dietary patterns are related to plasma concentrations of markers of inflammation and endothelial dysfunction. Am J Clin Nutr 2004; 80(4):1029-1035..

An MA⁸8 Fabiani R, Naldini G, Chiavarini M. Dietary Patterns and Metabolic Syndrome in Adult Subjects: A Systematic Review and Meta-Analysis. Nutrients 2019; 11(9):2056. conducted with the inclusion of studies carried out in countries located in America, Asia and, Europe, assessed the relationship between gender, dietary pattern, and MetS, which did not verify the association of dietary pattern with MetS. However, it was observed that the “healthy” dietary pattern determined a stronger protective effect for women⁸8 Fabiani R, Naldini G, Chiavarini M. Dietary Patterns and Metabolic Syndrome in Adult Subjects: A Systematic Review and Meta-Analysis. Nutrients 2019; 11(9):2056.. In the present MA, dietary patterns from two countries in the American continent (USA and Brazil), from one European country, and a set of countries in Asia were combined, each one of them with relative characteristics feeding behaviors very different from each other, originated from their distinct eating cultures. Nevertheless, the majority of the studies were concentrated in the USA, a fact that denotes insufficient scientific interest in the theme, mainly, when it refers to women and Afro-descendant populations.

In addition to the issue related to gender and ethnicity, another important aspect that needs to be better assessed by further studies and, which possibly influenced the results presented hereby, concerns the environmental and socio-economic factors, given that the regions of lower economic development, inserted in food deserts and scenarios of social vulnerability, are marked by restricted access to a healthy diet, with low intake of fruit, vegetables, legumes, and fish and, on the other hand, with high intake of processed meat¹⁷17 Couch CA, Gray MS, Shikany JM, Howard VJ, Howard G, Long DL, McClure LA, Manly JJ, Cushman M, Zakai NA, Pearson KE, Levitan EB, Judd SE. Correlates of a southern diet pattern in a national cohort study of blacks and whites: the REasons for Geographic And Racial Differences in Stroke (REGARDS) study. Br J Nutr 2021; 126(12):1904-1910.^,5858 Morland K, Wing S, Diez RA, Poole C. Neighborhood characteristics associated with the location of food stores and food service places. Am J Prev Med 2002; 22(1):23-29.^,5959 Diez-Roux A V, Nieto J, Caulfield L, Tyroler HA, Watson RL, Szklo M. Neighbourhood diVerences in diet: the Atherosclerosis Risk in Communities (ARIC) Study. J Epidemiol Community Heal 1999; 53:55-63.. Thus, more studies that approach socio-economic and environmental factors related to dietary patterns and MetS are necessary.

The analyses presented in this study denoted the existence of different levels of heterogeneity among the analyzed studies, which can be attributed to the peculiar characteristics (nutritional status, scholarship, socio-economic level) of the different populations investigated, to regional differences in the research due to the diverse locations where the studies were carried out, or to the different study designs, different food that composed the dietary patterns, and to the distinct statistical analyses conducted⁶⁰60 Figueiredo AC, Gomes-Filho IS, Silva RB, Pereira PP, Mata FA, Lyrio AO, Souza ES, Cruz SS, Pereira MG. Maternal Anemia and Low Birth Weight: A Systematic Review and Meta-Analysis. Nutrients 2018; 10(5):601..

Regarding the association between healthy dietary patterns and MetS-RF, the analyses of this study based on NutriGrade indicated very low evidence strength for the Women Population and for the Afro-descendant Population, while there was moderate evidence strength for the General Population. In contrast, the evidence strength when assessing the associations with unhealthy dietary patterns was classified as moderate for all groups. An MA involving cohort studies found moderate evidence strength in the associations between diet quality (reflecting healthy dietary patterns) and multiple health outcomes⁶¹61 Morze J, Danielewicz A, Hoffmann G, Schwingshackl L. Diet Quality as Assessed by the Healthy Eating Index, Alternate Healthy Eating Index, Dietary Approaches to Stop Hypertension Score, and Health Outcomes: A Second Update of a Systematic Review and Meta-Analysis of Cohort Studies. J Acad Nutr Diet 2020; 120(12):1998-2031.e15.. Such a result is similar to the one found in this study for General Population as to the healthy dietary pattern.

It is highlighted that when this pattern was assessed for the Women Population and for the Afro-descendant population the number of manuscripts inserted in the MA was lesser, which may have led to very low evidence. In addition, other aspects that contributed to this were the high heterogeneity, presence of publication bias, and small effect sample. This discussion is important because in, MA studies, the assessment of evidence quality is an important factor for planning nutritional recommendations based on reliable evidence⁶¹61 Morze J, Danielewicz A, Hoffmann G, Schwingshackl L. Diet Quality as Assessed by the Healthy Eating Index, Alternate Healthy Eating Index, Dietary Approaches to Stop Hypertension Score, and Health Outcomes: A Second Update of a Systematic Review and Meta-Analysis of Cohort Studies. J Acad Nutr Diet 2020; 120(12):1998-2031.e15.. In this context, in a general way, evidence from moderate to high magnitude is considered acceptable to make recommendations in health promotion interventions⁶¹61 Morze J, Danielewicz A, Hoffmann G, Schwingshackl L. Diet Quality as Assessed by the Healthy Eating Index, Alternate Healthy Eating Index, Dietary Approaches to Stop Hypertension Score, and Health Outcomes: A Second Update of a Systematic Review and Meta-Analysis of Cohort Studies. J Acad Nutr Diet 2020; 120(12):1998-2031.e15.^,6262 Andrews JC, Schünemann HJ, Oxman AD, Pottie K, Meerpohl JJ, Coello PA, Rind D, Montori VM, Brito JP, Norris S, Elbarbary M, Post P, Nasser M, Shukla V, Jaeschke R, Brozek J, Djulbegovic B, Guyatt G. GRADE guidelines: 15. Going from evidence to recommendation - determinants of a recommendation's direction and strength. J Clin Epidemiol 2013; 66(7):726-735.. Thus, the evidence found here for an unhealthy dietary pattern suggests that should be adopted at a strong recommendation level.

From the findings in the present SR-MA, it is identified the necessity of further studies on the Women Population and Afro-descendant Population to better elucidate the association between dietary patterns and MetS and its risk factors and, in addition, to assess which are the food that is part of the food culture of this public in the different regions worldwide, allowing health promotion interventions appropriate to different realities.

This study presents certain limitations, such as heterogeneity of the characteristic of the studies; the studies designs used to measure the exposure and dietary patterns; the scarcity of studies with the same dietary pattern and that presented data for the women and Afro-descendant populations; the presence of publication bias and; lastly, the grouped data used for the statistical analysis having already been calculated directly in the primary studies.

This study utilized different designs, including cross-sectional, case-control, and cohort studies, each with varying methods of data collection and analysis, resulting in different measures of association and frequency, which may constitute a limitation of the work. However, subgroups were analysed based on these designs to better understand the relationships between dietary patterns, ethnicities, gender, and MetS-RF. It should be emphasized that gender and ethnicity were not distinguished in the analysis, which is consistent with other meta-analyses⁷7 Godos J, Bella F, Torrisi A, Sciacca S, Galvano F, Grosso G. Dietary patterns and risk of colorectal adenoma: a systematic review and meta-analysis of observational studies. J Hum Nutr Diet 2016; 29(6):757-767.^,88 Fabiani R, Naldini G, Chiavarini M. Dietary Patterns and Metabolic Syndrome in Adult Subjects: A Systematic Review and Meta-Analysis. Nutrients 2019; 11(9):2056.. Cross-sectional studies can establish statistical associations and provide an instant view of the situation, but there is weakness in establishing causal inference due to the possibility of temporality bias. Cohort studies, on the other hand, are more suitable for establishing causal relationships, as they are prospective in nature and measure incidence, with the outcome necessarily occurring after exposure.

The strengths of this work are the usage of validated research techniques and instruments, such as the EPHPP²⁴24 Thomas BH, Ciliska D, Dobbins M, Micucci S. A process for systematically reviewing the literature: providing the research evidence for public health nursing interventions. Worldviews Evidence Based Nurs 2004; 1(3):176-184. used to assess the quality of the studies; the usage of PRISMA at the elaboration of the protocol of the present review and; the use of NutriGrade to assess the evidence quality. This one, despite its aims in the assessment of cohort studies and randomized clinical trials, has also been used in meta-analyses that include cross-sectional studies and case-control studies in parallel with cohort studies⁶³63 Yu J, Balaji B, Tinajero M, Jarvis S, Khan T, Vasudevan S, Ranawana V, Poobalan A, Bhupathiraju S, Sun Q, Willett W, Hu FB, Jenkins DJA, Mohan V, Malik VS. White rice, brown rice and the risk of type 2 diabetes: a systematic review and meta-analysis. BMJ Open 2022; 12(9):e065426.

64 Rodrigues C, Pinto A, Faria A, Teixeira D, van Wegberg AM, Ahring K, Feillet F, Calhau C, Macdonald A, Moreira-Rosário A, Rocha JC. Is the phenylalanine-restricted diet a risk factor for overweight or obesity in patients with phenylketonuria (Pku)? A systematic review and meta-analysis. Nutrients 2021; 13(10):3443.^-6565 Schwingshackl L, Hoffmann G, Lampousi AM, Knüppel S, Iqbal K, Schwedhelm C, Bechthold A, Schlesinger S, Boeing H. Food groups and risk of type 2 diabetes mellitus: a systematic review and meta-analysis of prospective studies. Eur J Epidemiol 2017; 32(5):363.. It is noteworthy the originality of the present study, which had as a focus and differential the inclusion of publications that had analyzed individuals of the women gender and of the Afro-descendant ethnicity.

It is concluded that a healthy dietary pattern decreases the odds of the development of MetS-RF, thus becoming an important protective factor against this aggravation in the general population. In contrast, an unhealthy dietary pattern is associated with higher odds for the development of outcomes related to such syndrome, both in the general population, regardless of sex and ethnicity, and in the women and Afro-descendant population, thus becoming a risk factor relevant. Such findings must be considered by public health professionals and managers to promote the adoption of healthy eating habits and life quality of the population, especially those who live under greater social vulnerability.

To better demonstrate the relationships between dietary patterns and MetS-RF, it is recommended that further studies be carried out involving, particularly, women and the Afro-descendant public, and that, in addition, identify which foods most characterize the food culture of this public in the different regions of the world and how much they can mediate these relationships.

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